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Tannenberg is a Fraktur-family blackletter typeface, developed between 1933 and 1935 by Erich Meyer at the type foundry D. Stempel AG in Frankfurt am Main. The design followed the "New Typography" principles of Jan Tschichold that promoted "constructed" sans serif typefaces. It is named after the Battle of Tannenberg in 1914, in which German troops under Paul von Hindenburg and Erich Ludendorff stopped the advance of Russian troops. Meyer's design for the typeface was inspired by Nazi ideology.[1]
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The Tannenberg font soon became very popular and was widely used. It was used on official stamps, in book and magazine design, in advertising and in Nazi Party propaganda.[3][4] From about 1935 to 1941, the Deutsche Reichsbahn used the Tannenberg typeface on station signs. These signs can still be seen on some stations of the Berlin North-South S-Bahn, which opened in 1936.[5]
Like all blackletter typefaces, Tannenberg was hardly used in official documents after Martin Bormann's "normal type decree" of 1941 ordered that Fraktur-style typefaces be no longer used. Nothing changed to reverse this policy with the end of the Nazi regime in 1945. However, in 1946, among other things, the "Stuttgart Declaration of Guilt" was published in the "Regulations and News Sheet of the Evangelical Church in Germany" in Tannenberg, Saxony.[6]
For each topic they then prompted GPT3 with key sentences from the real propaganda, and some propaganda articles on unrelated topics to use as models, to generate 3 novel, AI generated, propaganda articles.
In addition to the comparison of pure-AI generated article, a follow up study used GPT3 generated articles with a human-improved prompt (rather text direct copied from a source article), with an additional step of a human selecting from the generated articles so only those which supported the thesis were included. These curated human-AI team articles were then tested, with the additional analysis looking at the performance when only the most persuasive articles from this set were included.
Reading propaganda doubled the percentage of people who agreed with the thesis, and the extend of agreement was only slightly higher for the original (human, professionally written) propaganda than the AI generated propaganda.
Pair with the real possibility that exaggerating the dangers of propaganda (from AI or not) has its own negative downstream effects, such as loss of faith in democracy and increased support for censorship, and I think we need to keep studies like this one in perspective.
According to the latest report prepared by the British Bureau of Investigative Journalism (BIJ), in Pakistan alone as many as 966 civilians were killed in total during the period between 2004 and 2016.
This report has been published after a thorough research conducted by this group. The group has also claimed that around two years ago, these attacks caused deaths of more than 10 people on daily basis. On average, seven people were killed on monthly basis and four on weekly basis.
A bullet review is my new invention. It means I\u2019m going to review a research study quickly, and give you my first impression. It\u2019s like the difference between standard chess and bullet chess, which is played under a severe time restriction. Also, I\u2019m going to use lots of headings and bullet points to structure the review.
They also found that the \u201Chuman-machine team\u201D allowed GPT3 to produce better outputs. It even looks like the best of these article outperformed the real, original, propaganda (very bottom data point in plot below):
AI generates effective propaganda, efficiently: \u201Cthe large language model can create highly persuasive text, and that a person fluent in English could improve the persuasiveness of AI-generated propaganda with minimal effort\u201D
AI generated propaganda is no worse for fluency than other propaganda: \u201CGPT-3-generated content could blend into online in\u00ADformation environments on par with content we sourced from ex\u00ADisting foreign covert propaganda campaigns\u201D
\u201Cour estimates may represent a lower bound on the relative persuasive potential of large language models\u201D. First AI is improving, and, second, in the real world people will get multiple exposures rather than one-shot.
This report has strong signs of good academic practice: there\u2019s a preregistered analysis plan, deviations from which are recorded. Full stimulus materials are shared, as is the full data and analysis code. Extensive supplementary materials give details on the procedures used. The report itself is clear and the analysis is a direct report of the results.
Just to get it out of the way, I don\u2019t believe the final comparison the author\u2019s present - that the \u201Cbest performing\u201D human-AI generated propaganda is better than propaganda found in the wild. Specifically, I don\u2019t believe the result means anything. The analysis of \u201Cbest performing outputs\u201D smuggles in the answer in the definition of the category. If you test various outputs, which vary in there effects, and then discard the ones with the lower performance it *has* to increase the average effect of the outputs remaining. It\u2019s like saying that AI always generates persuasive propaganda except when it doesn\u2019t. The authors don\u2019t make much of this comparison, and their main claims don\u2019t depend on it, so let\u2019s just agree not to mention it again.
Another reason not to trust the result is the low commitment scenario of the participants. The quality of responding of online samples can be notoriously patchy. Yes, they exclude people who failed checks of whether they were even reading the questions, but still the study is done by people we know remarkably little about, clicking through some screens of text and then indicating their feelings on a five point scale. When they say they agree with the claims, what do they really mean? Would they make bets on based on their beliefs? Change their voting? We don\u2019t know, and I suspect their involvement in the issues is pretty thin.
The presentation of the articles, and the control condition, also raise the spectre that participants are responding to the demands of the scenario rather than being particularly persuaded by the articles. Remember, in the control condition participants didn\u2019t read anything, they just answered the questions. For the propaganda questions participants were asked to read an article which - essentially - claimed X and then asked \u201Cdo you agree that X?\u201D. On average participants were more likely to agree after being told that something was the case, and I think you could make a case that this is an entirely reasonable response, particularly for participants who aren\u2019t very invested either way. Basically, I can imagine a participant thinking \u201CYou just told me that X is the case, so I guess I agree it might be\u201D.
The premise of this newsletter is that people are more reasonable than often portrayed. This isn\u2019t to deny that propaganda exists, and false beliefs, and foolishness - just that there\u2019s good news about human rationality as well as bad.
Unsurprisingly, I\u2019m cautious about this study as evidence of the effectiveness of propaganda. It really doesn\u2019t test anything like the effects we are concerned about - effects which persist over time (rather than being immediate), which persuade people to abandon old beliefs and adopt new ones, and/or adopt costly novel behaviours (like invading government buildings, betraying their neighbours, supporting wars etc). The study evidence is consistent with propaganda being able to do those things, but doesn\u2019t give me more reason to believe it does.
Hugo Mercier (in this 2017 article \u201CHow Gullible are We? A Review of the Evidence from Psychology and Social Science\u201D and his book \u201CNot Born Yesterday: The Science of Who We Trust and What We Believe\u201D) takes on the case of propaganda directly, arguing that the historical cases of the effectiveness of propaganda are wildly exaggerated. Once you take out the effects of propaganda encouraging people to express what they already believe, to coordinate with each other around those beliefs, and for government to signal what is acceptable for citizens to believe, Mercier argues, there isn\u2019t any good evidence that *anyone* is ever persuaded by propaganda.
This isn\u2019t evidence that such propaganda is persuasive. Fundamentally the study uses a very superficial measure - professed agreement - from a low-engagement sample. This isn\u2019t a strong test of actual effect on enduring beliefs. 152ee80cbc
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